The pharmaceutical industry is facing a demand for more sustainable, cost-effective, and environmentally friendly manufacturing processes. A key challenge is the reduction of waste streams. Crystallization is a key technology within almost any pharmaceutical process. Although crystallization allows to obtain a high-purity product within a single operating step, significant waste streams may be generated. Currently there is a high interest to investigate novel technologies that can be used to upgrade waste streams to products. In particular, membrane technology can be used to recover pure water from an aqueous waste stream with pharmaceuticals (so-called membrane-assisted crystallization). Besides pure water, an additional stream enriched with pharmaceuticals can be obtained that can be recycled to the crystallizer to improve product yield, which ultimately may result in a zero-waste process. However, adding additional processing steps and recycle streams also increases the complexity. The aim of this UROP project is to investigate via numerical simulations particular types of complicated process behavior (e.g., multiple steady states) that may exist for this novel membrane-assisted crystallization processes. The current lack in understanding of at least the qualitative process behavior hinders the introduction of this novel technology to reduce waste streams in pharmaceutical industry. This project is particularly suitable for students with an interest in mathematical programming and/or linear algebra.

Course type:

UROP1100 UROP2100 UROP3100 UROP4100

Applicant's Roles:

A mathematical model including explanation of variables and parameters will be provided for the described process as well as a basic implementation in computational software of choice (e.g., Matlab). The student is expected to analyze (the mathematical characteristics of) this process model using numerical simulations and derive implications for design. Specific knowledge of this topic is not required, but a general interest in mathematical programming and/or linear algebra is beneficial. Relevant literature resources will be provided.

Applicant's Learning Objectives:

1) Formulate the mathematical conditions under which certain types of complicated process behavior occurs based on literature review.
2) Develop a computational code that maps a certain type of complicated process behavior (e.g., state multiplicity) as function of a process variable for the given case if it exists.
3) Discuss the implications of any identified complicated process behavior for design and operation.